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PubMed1999

JPEG quality transcoding using neural networks trained with a perceptual error measure.

A JPEG Quality Transcoder (JQT) converts a JPEG image file that was encoded with low image quality to a larger JPEG image file with reduced visual artifacts, without access to the original uncompressed image. In this article, we describe technology for JQT design that takes a pattern recognition approach to the problem, using a database of images to train statistical models of the artifacts introduced through JPEG compression. In the training procedure for these models, we use a model of human visual perception as an error measure. Our current prototype system removes 32.2% of the artifacts introduced by moderate compression, as measured on an independent test database of linearly coded images using a perceptual error metric. This improvement results in an average PSNR reduction of 0.634 dB.

Algorithms↗

PubMed2006

Representation and timing in theories of the dopamine system.

Although the responses of dopamine neurons in the primate midbrain are well characterized as carrying a temporal difference (TD) error signal for reward prediction, existing theories do not offer a credible account of how the brain keeps track of past sensory events that may be relevant to predicting future reward. Empirically, these shortcomings of previous theories are particularly evident in their account of experiments in which animals were exposed to variation in the timing of events. The original theories mispredicted the results of such experiments due to their use of a representational device called a tapped delay line. Here we propose that a richer understanding of history representation and a better account of these experiments can be given by considering TD algorithms for a formal setting that incorporates two features not originally considered in theories of the dopaminergic response: partial observability (a distinction between the animal's sensory experience and the true underlying state of the world) and semi-Markov dynamics (an explicit account of variation in the intervals between events). The new theory situates the dopaminergic system in a richer functional and anatomical context, since it assumes (in accord with recent computational theories of cortex) that problems of partial observability and stimulus history are solved in sensory cortex using statistical modeling and inference and that the TD system predicts reward using the results of this inference rather than raw sensory data. It also accounts for a range of experimental data, including the experiments involving programmed temporal variability and other previously unmodeled dopaminergic response phenomena, which we suggest are related to subjective noise in animals' interval timing. Finally, it offers new experimental predictions and a rich theoretical framework for designing future experiments.

Algorithms↗

PubMed1990

Estimation of the probability of disturbed breathing during sleep before a sleep study.

We have investigated the ability of a statistical model developed from clinical data and questionnaire responses to predict disturbance of breathing during sleep. Data from 100 consecutive patients referred for sleep study for suspected sleep apnea were used to develop the model using logistic regression analysis. For each subject, the model predicted the probability of having an apnea-hypopnea index (AHI) greater than 15; this probability was compared with the AHI measured from sleep study. A probability cutoff point (= 0.15) was decided on that minimized the number of subjects with false-negative predictions. Four terms--apneas observed by bed partner, hypertension, body mass index, and age--were found to contribute significantly to the model with observed apneas being by far the most predictive term of the four (adjusted odds ratio 19.7). When the model was tested to estimate the probability of an AHI greater than 15 for 105 patients from a second group of consecutive patients referred for sleep study, the model correctly classified 33 of 36 patients with a measured AHI greater than 15 (sensitivity = 92%) and 35 of 69 patients with a measured AHI less than or equal to 15(specificity = 51%). This study shows that analysis of clinical features of patients presenting with suspected sleep apnea may reduce the need for sleep studies by about one-third yet still lead to the identification of the great majority of patients with abnormal breathing during sleep.

Female↗

PubMed2002

Full identification of a linear-nonlinear system via cross-correlation analysis.

A statistical model used extensively in vision research consists of a cascade of a linear operator followed by a static (memoryless) nonlinearity. Common applications include the measurement of simple-cell receptive fields in primary visual cortex and the modeling of human performance in various psychophysical tasks. It is well known that the front-end linear filter of the model can readily be recovered, up to a multiplicative constant, using reverse-correlation techniques. However, a full identification of the model also requires an estimation of the output nonlinearity. Here, we show that for a large class of static nonlinearities, one can obtain analytical expressions for the estimates. The technique works with both Gaussian and binary noise stimuli. The applicability of the method in physiology and psychophysics is demonstrated. Finally, the proposed technique is shown to converge much faster than the currently used linear-reconstruction method.

Humans↗

PubMed1998

Sleep disturbances in the Vietnam generation: findings from a nationally representative sample of male Vietnam veterans.

OBJECTIVE: This study analyzed questionnaire items that address complaints about sleep from the National Vietnam Veterans Readjustment Study, a nationally representative sample of the 3.1 million men and women who served in Vietnam. This study compared the frequency of nightmares and difficulties with sleep onset and sleep maintenance in male Vietnam theater veterans with male Vietnam era veteran and male civilian comparison subjects. It focused on the role of combat exposure, nonsleep posttraumatic stress disorder (PTSD) symptoms, comorbid psychiatric and medical disorder, and substance abuse in accounting for different domains of sleep disturbance. METHOD: The authors undertook an archival analysis of the National Vietnam Veterans Readjustment Study database using correlations and linear statistical models. RESULTS: Frequent nightmares were found exclusively in subjects diagnosed with current PTSD at the time of the survey (15.0%). In the sample of veterans who served in Vietnam (N = 1,167), combat exposure was strongly correlated with frequency of nightmares, moderately correlated with sleep onset insomnia, and weakly correlated with disrupted sleep maintenance. A hierarchical multiple regression analysis showed that in Vietnam theater veterans, 57% of the variance in the frequency of nightmares was accounted for by war zone exposure and non-sleep-related PTSD symptoms. Alcohol abuse, chronic medical illnesses, panic disorder, major depression, and mania did not predict the frequency of nightmares after control for nonsleep PTSD symptoms. CONCLUSIONS: Frequent nightmares appear to be virtually specific for PTSD. The nightmare is the domain of sleep disturbance most related to exposure to war zone traumatic stress.

Combat Disorders↗

PubMed2004

Evaluation of treatment programs for persons with severe mental illness: moderator and mediator effects.

This study evaluated several statistical models for estimating treatment effects in a randomized, longitudinal experiment comparing assertive community treatment (ACT) versus brokered case management (BCM). In addition, mediator and moderator analyses were conducted. The ACT clients had improved outcomes in terms of housing and psychiatric symptoms than BCM clients. Case management housing assistance and financial assistance partially mediated housing outcomes. No reliable mediators were found for psychiatric symptoms, and no reliable moderators were found for either housing or psychiatric symptoms. The study also made several important methodological advances in the analysis of longitudinal data in randomized experiments.

Adult↗

PubMed2004

A statistical evaluation of the fixed dose procedure.

The Fixed Dose Procedure (FDP) was first proposed in 1984 by the British Toxicology Society, as an alternative to the conventional LD50 test (OECD Test Guideline 401), for determining acute oral toxicity. The FDP used fewer animals and caused less suffering than the LD50 test, and provided information on acute toxicity which allowed substances to be classified according to the European Union hazard classification system. In 1992, the FDP was introduced as OECD Test Guideline 420. In 1999, as part of an initiative to phase out Test Guideline 401, a review of the FDP was undertaken. The aim of the review was to provide further reductions and refinements, and classification according to the criteria of the Globally Harmonised Hazard Classification and Labelling Scheme. The revised FDP was adopted by the OECD in 2001. This article concerns the development and revision of the FDP. It illustrates how statistical modelling and simulation can be used to increase the efficiency of a test procedure and reduce the number of animals needed for an in vivo validation of the procedure.

Animal Use Alternatives↗

PubMed2004

Opportunities for reduction in acute toxicity testing via improved design.

The conventional method for assessing acute oral toxicity (OECD Test Guideline 401) was designed to identify the median lethal dose (LD50), using the death of animals as an endpoint. Introduced as an alternative method (OECD Test Guideline 420), the Fixed Dose Procedure (FDP) relies on the observation of clear signs of toxicity, uses fewer animals and causes less suffering. More recently, the Acute Toxic Class method and the Up-and-Down Procedure have also been adopted as OECD test guidelines. Both of these methods also use fewer animals than the conventional method, although they still use death as an endpoint. Each of the three new methods incorporates a sequential dosing procedure, which results in increased efficiency. In 1999, with a view to replacing OECD Test Guideline 401, the OECD requested that the three new test guidelines be updated. This was to bring them in line with the regulatory needs of all OECD Member Countries, provide further reductions in the number of animals used, and introduce refinements to reduce the pain and distress experienced by the animals. This paper describes a statistical modelling approach for the evaluation of acute oral toxicity tests, by using the revised FDP for illustration. Opportunities for further design improvements are discussed.

Animal Use Alternatives↗

PubMed1996

Screening for clinical laboratory errors with Medicare claims data: results for digoxin.

A statistical model is demonstrated for finding outpatient clinical laboratories having high frequencies of bad patient outcomes, after testing, that may indicate testing errors. A sample of Medicare Part A and Part B claims for 30,685 digoxin tests for 1985 through 1987 was analyzed. Deaths or digoxin-related hospitalizations within 14 days of digoxin testing are defined as "adverse events" potentially influenced by test information. Approximately 3.3% of digoxin tests were followed by adverse events with two-thirds resulting in hospitalization or death. Adverse events were (a) lower in states with stronger laboratory regulations, (b) 15% higher whenever the site of testing switched, (c) unrelated to testing in low volume physician office laboratories, and (d) unrelated to frequency of digoxin testing in previous 6 months. Results a and b are consistent with findings for prothrombin testing but c and d are not. Differences are consistent with technical characteristics of the tests.

Anti-Arrhythmia Agents↗

PubMed1992

A statistical study of factors influencing outpatient service in health districts.

This paper describes a statistical study within NHS health districts, using routinely available data, of the supply of outpatient services, the demands made on these services and the resulting balance of supply and demand. Indicators of supply have been investigated which aim to reflect the resources available within a district for outpatient services and indicators of demand have been studied which link to the number of general practitioners who are considered likely to make use of the services provided. Some preliminary analysis is attempted of relationships between the observed balance of supply and demand and the predictions based on the statistical models developed.

Ambulatory Care↗

PubMed1999

Determinants of hospital bad debt: multivariate statistical analysis.

Although the issue of uncompensated care (bad debt plus charity care) has been actively debated in the public arena, there has been little discussion of the bad debt issue alone. This issue is important since issues of bad debt, charity care and uncompensated care are significantly different from each other. Based on 1992 State of Missouri data, the results of our study indicate that more efficient hospitals (measured by occupancy rate), hospitals with more patients covered by prospective payment systems (measured by Medicare discharges), and for-profit hospitals incurred significantly less bad debt cost than other hospitals. However, the difference in bad debt between for-profit hospitals and not-for-profit hospitals is dissipated when using a multivariate statistical model. In addition, this study also reveals that hospitals which provide more charity care have the lowest bad debt costs. Policy implications are also discussed.

Charities↗

PubMed1993

Analysis of DNA sequences.

Recent developments in the statistical analysis of DNA sequences are reviewed. The pace with which sequence data are being generated and analysed has increased with the growth of the human genome project. Two areas of activity are emphasized: attention to error rates in recorded sequences, and heterogeneity in structure of sequences. There is now empirical evidence suggesting error rates in the range 0.1%-1%, and such rates will affect evolutionary studies since these are about the rates at which DNA sequences from different individuals are expected to differ. Heterogeneity for such quantities as base composition, or lengths between successive subsequences of specified types, may be sufficient to account for observed long-range correlations between bases. The need for statistical models and analyses of DNA sequence data will continue, and will offer interesting challenges.

Algorithms↗

PubMed2006

Demonstration of two novel methods for predicting functional siRNA efficiency.

BACKGROUND: siRNAs are small RNAs that serve as sequence determinants during the gene silencing process called RNA interference (RNAi). It is well know that siRNA efficiency is crucial in the RNAi pathway, and the siRNA efficiency for targeting different sites of a specific gene varies greatly. Therefore, there is high demand for reliable siRNAs prediction tools and for the design methods able to pick up high silencing potential siRNAs. RESULTS: In this paper, two systems have been established for the prediction of functional siRNAs: (1) a statistical model based on sequence information and (2) a machine learning model based on three features of siRNA sequences, namely binary description, thermodynamic profile and nucleotide composition. Both of the two methods show high performance on the two datasets we have constructed for training the model. CONCLUSION: Both of the two methods studied in this paper emphasize the importance of sequence information for the prediction of functional siRNAs. The way of denoting a bio-sequence by binary system in mathematical language might be helpful in other analysis work associated with fixed-length bio-sequence.

Algorithms↗

PubMed2005

Empirical evaluation of prediction intervals for cancer incidence.

BACKGROUND: Prediction intervals can be calculated for predicting cancer incidence on the basis of a statistical model. These intervals include the uncertainty of the parameter estimates and variations in future rates but do not include the uncertainty of assumptions, such as continuation of current trends. In this study we evaluated whether prediction intervals are useful in practice. METHODS: Rates for the period 1993-97 were predicted from cancer incidence rates in the five Nordic countries for the period 1958-87. In a Poisson regression model, 95% prediction intervals were constructed for 200 combinations of 20 cancer types for males and females in the five countries. The coverage level was calculated as the proportion of the prediction intervals that covered the observed number of cases in 1993-97. RESULTS: Overall, 52% (104/200) of the prediction intervals covered the observed numbers. When the prediction intervals were divided into quartiles according to the number of cases in the last observed period, the coverage level was inversely proportional to the frequency (84%, 52%, 46% and 26%). The coverage level varied widely among the five countries, but the difference declined after adjustment for the number of cases in each country. CONCLUSION: The coverage level of prediction intervals strongly depended on the number of cases on which the predictions were based. As the sample size increased, uncertainty about the adequacy of the model dominated, and the coverage level fell far below 95%. Prediction intervals for cancer incidence must therefore be interpreted with caution.

Adolescent↗

PubMed2006

Occurrence of invasive pneumococcal disease and number of excess cases due to influenza.

BACKGROUND: Influenza is characterized by seasonal outbreaks, often with a high rate of morbidity and mortality. It is also known to be a cause of significant amount secondary bacterial infections. Streptococcus pneumoniae is the main pathogen causing secondary bacterial pneumonia after influenza and subsequently, influenza could participate in acquiring Invasive Pneumococcal Disease (IPD). METHODS: In this study, we aim to investigate the relation between influenza and IPD by estimating the yearly excess of IPD cases due to influenza. For this purpose, we use influenza periods as an indicator for influenza activity as a risk factor in subsequent analysis. The statistical modeling has been made in two modes. First, we constructed two negative binomial regression models. For each model, we estimated the contribution of influenza in the models, and calculated number of excess number of IPD cases. Also, for each model, we investigated several lag time periods between influenza and IPD. Secondly, we constructed an "influenza free" baseline, and calculated differences in IPD data (observed cases) and baseline (expected cases), in order to estimate a yearly additional number of IPD cases due to influenza. Both modes were calculated using zero to four weeks lag time. RESULTS: The analysis shows a yearly increase of 72-118 IPD cases due to influenza, which corresponds to 6-10% per year or 12-20% per influenza season. Also, a lag time of one to three weeks appears to be of significant importance in the relation between IPD and influenza. CONCLUSION: This epidemiological study confirms the association between influenza and IPD. Furthermore, negative binomial regression models can be used to calculate number of excess cases of IPD, related to influenza.

Disease Susceptibility↗

PubMed2004

Assessing the impact of heart failure specialist services on patient populations.

BACKGROUND: The assessment of the impact of healthcare interventions may help commissioners of healthcare services to make optimal decisions. This can be particularly the case if the impact assessment relates to specific patient populations and uses timely local data. We examined the potential impact on readmissions and mortality of specialist heart failure services capable of delivering treatments such as b-blockers and Nurse-Led Educational Intervention (N-LEI). METHODS: Statistical modelling of prevented or postponed events among previously hospitalised patients, using estimates of: treatment uptake and contraindications (based on local audit data); treatment effectiveness and intolerance (based on literature); and annual number of hospitalization per patient and annual risk of death (based on routine data). RESULTS: Optimal treatment uptake among eligible but untreated patients would over one year prevent or postpone 11% of all expected readmissions and 18% of all expected deaths for spironolactone, 13% of all expected readmisisons and 22% of all expected deaths for b-blockers (carvedilol) and 20% of all expected readmissions and an uncertain number of deaths for N-LEI. Optimal combined treatment uptake for all three interventions during one year among all eligible but untreated patients would prevent or postpone 37% of all expected readmissions and a minimum of 36% of all expected deaths. CONCLUSION: In a population of previously hospitalised patients with low previous uptake of b-blockers and no uptake of N-LEI, optimal combined uptake of interventions through specialist heart failure services can potentially help prevent or postpone approximately four times as many readmissions and a minimum of twice as many deaths compared with simply optimising uptake of spironolactone (not necessarily requiring specialist services). Examination of the impact of different heart failure interventions can inform rational planning of relevant healthcare services.

Adrenergic beta-Antagonists↗

PubMed2026

Enhancing detection of polygenic adaptation: a comparative study of machine learning and statistical approaches using simulated evolve-and-resequence data.

BACKGROUND: Detecting signals of polygenic adaptation remains a significant challenge in population genomics, as traditional methods often struggle to identify the associated subtle, multi-locus allele-frequency shifts. Here, we introduced and tested several novel approaches combining machine learning techniques with traditional statistical tests to detect polygenic adaptation patterns in time-series of allele frequency changes from whole genome data. We implemented a Naive Bayesian Classifier (NBC) and One-Class Support Vector Machines (OCSVM), and compared their performance against the classical Fisher's Exact Test (FET). Furthermore, we combined machine learning and statistical models (OCSVM-FET and NBC-FET), resulting in 5 competing approaches. The framework is mainly designed and validated for evolve-and-resequence (EaR) experimental designs, where defined selection pressures and temporal sampling are feasible, but might be applicable for certain natural experiments as well. RESULTS: Using a simulated dataset based on empirical C. riparius Pool-Seq data, we evaluated methods across evolutionary scenarios varying in generation, selection strength, and number of loci under selection. Our results demonstrate that the combined OCSVM-FET approach consistently outperformed competing methods, achieving the lowest false positive rate, highest area under the curve, and high accuracy. The performance peak aligned with what we term the 'late dynamic phase' of adaptation - the period after initial selection has occurred but before fixation - highlighting the method's sensitivity to ongoing selective processes. CONCLUSIONS: Furthermore, we emphasize the critical role of parameter tuning, balancing biological assumptions with methodological rigor. While broader applicability remains an important direction for future work, the present benchmarking is intentionally scoped to EaR experimental contexts.

Machine Learning↗

PubMed2006

Determinants of physical health in frail older people: the importance of self-efficacy.

OBJECTIVE: There is continued uncertainty regarding the strength of association between performance-based and self-report measures of physical functioning, and of their relationship to self-efficacy and health-related quality of life (HRQoL). This study assessed the inter-relationships between such measures, and the predictors of 'physical' aspects of HRQoL in frail older patients. DESIGN: We used statistical models to determine the predictors of 'physical' HRQoL, according to the physical component summary score and the physical functioning domain of the 36-item short form (SF-36) questionnaire. SETTING: Patients were recruited from hospitals in Australia and New Zealand and followed up in their homes. SUBJECTS: Two hundred and forty-three frail older patients. MAIN MEASURES: Physical functioning was assessed using three performance-based measures (Timed Up and Go Test, gait speed and the Berg Balance Scale) and five self-report measures, including the modified falls self-efficacy scale, at three and six months after registration. RESULTS: A moderate association (r = 0.48-0.55) was found between each of the performance-based and self-report measures, including the SF-36 physical component summary score. Multiple linear regression analyses showed that the performance-based measures and falls self-efficacy predicted 33% of the SF-36 physical component summary score. Falls self-efficacy was the single highest predictor of both the SF-36 physical component summary score and SF-36 physical functioning domain. A curvilinear relationship was found between the SF-36 physical functioning domain and two variables: falls self-efficacy and the Berg Balance Scale. CONCLUSIONS: Although performance-based and self-report measures provide complementary but distinct measures of physical function, psychosocial factors such as self-efficacy have a strong influence on the HRQoL of frail older people.

Activities of Daily Living↗